AI-Augmented Software Engineer

Ovrsea is a next-generation digital freight forwarder on a mission to reinvent international transport. We combine human expertise with powerful technology to make global logistics simpler, more transparent, and more efficient for shippers around the world.

Over the past few years, Ovrsea has grown fast — now 50+ offices across 13 countries — and operates at the crossroads of global logistics, software, and AI.

Our ambition: build the most advanced, AI-augmented freight-forwarding platform in the industry.

About the team

Our tech team builds the systems that power international freight operations end-to-end: multimodal quotations, shipment orchestration, predictive ETAs, document management, billing, and deeply integrated business workflows.

We care deeply about developer experience and engineering velocity.

We ship fast (around 20 deployments per day), maintain short feedback loops, and are fully aligned with Accelerate principles: small batch sizes, continuous delivery, strong automation, and a culture of learning.

As we accelerate the transition toward an AI-augmented company, we are opening a new, exploratory, high-potential role.

About the role

We're looking for a Junior Software Engineer with an AI-native mindset — someone who naturally uses AI tools to accelerate their work, explore ideas fast, and solve problems creatively.

Your mission: Use AI as a force multiplier across engineering and the business.

This means:

- making engineers more productive,

- improving internal processes,

- simplifying operational workflows,

- and exploring any use case where AI can save time or reduce complexity.

This is not an "LLM product" or "ML research" role. It's a builder role: someone who codes, prototypes, experiments, and ships internal improvements that genuinely make life easier for the team.

Because this is exploratory, we're intentionally keeping the scope broad to discover exceptional AI-fluent junior talent.

 What you'll do

- Use AI tools (Cursor, ChatGPT, Claude, Copilot…) to boost engineering velocity

- Build small internal tools that automate repetitive tasks or streamline workflows

- Improve developer experience (scripts, bots, CLI tools, code generators, documentation helpers)

- Explore AI opportunities across the business (Ops, Sales, Customer Success)

- Prototype quickly, iterate fast, and validate ideas with real users

- Spot inefficiencies and propose pragmatic, AI-assisted solutions

- Contribute to backend, frontend, or internal tooling depending on your strengths

You're not expected to know everything — only to learn fast and build fast.

 Who we're looking for

Someone who is early in their career, but already:

- comfortable coding in TypeScript and/or Python

- naturally uses AI in their daily workflow

- curious, resourceful, and excited by ambiguous problems

- capable of turning ideas into prototypes quickly

- motivated by real internal impact, not theoretical research

- pragmatic: you care about solving problems, not building complex systems

- collaborative: you'll work closely with engineers, PMs, and operations

Nice to have:

- you've built bots, scripts, tools, or scrappy side projects

- you've automated something for fun or to save time

- you've played with RAG, agents, embeddings, or data assistants

Examples of possible projects

(Examples only — you will help define the real ones.)

- Automating engineering chores (PR templates, changelog generation, data scrapers)

- Creating small internal dashboards or assistants for Ops or Sales

- Streamlining onboarding through AI-assisted documentation

- Improving CI/CD workflows using AI-generated configs or checks

- Code search assistants

- Tools that reduce cognitive load for engineers or operators

The spirit is: identify friction → reduce it → ship.

 Why join Ovrsea

- Work directly with senior engineers and product teams

- Contribute to Ovrsea's transition into an AI-augmented company

- High autonomy and fast iteration cycles

- Real impact on how 1000+ people work every day

- A culture that values pragmatism, experimentation, and learning

- A company combining scale-up robustness with startup energy

 Hiring process

Screening call – Meet with Antoine (CTO) and Nicolas (Head of Engineering)

Live coding test – 60 minutes, practical software engineering

AI + Technical Case Interview – Engineering reasoning, problem-solving, use of AI

Speed recruiting – Meet 4 team members from Engineering, Product, and Ops

Reference checks